Developing a Spatial Mathematical Model for Assessing the Rate of Natural Forest Changes

Abstract

Establishing a spatial mathematical model that uses diverse data types such as ratio data, interval data, and ordinal and nominal data is a challenge. This paper describes how the mathematical model of the rate of natural forest cover change was developed by considering the causes and/or driving forces that come from the society's biophysical and/or socioeconomic aspects. The main objective of this research is to establish a spatial mathematical model using the environmental and socioeconomic variables that play a significant role in determining the rate of natural forest cover change. From a number of variables considered in the analysis, coupled with any other reason, the rate of natural forest cover change (y), in units of ha per year), this study found that there are 10 potential variables, namely the proximity of the road (x4), the proximity of the river (x5), the proximity of the settlement (x6), proximity from the regency capital (x8), the proximity of the capital city of the district (x9), proximity of the edge of the forest in 2015 (x11), the proximity of the plantation area in 2009 (x12), the proximity of the plantation in 2015 (x13), slope class (x16), and elevation class (x17). The standardization process successfully transformed the non-ratio data type into a ratio data type. Using the standardized data, the study obtained spatially mathematical models that are reliable in estimating the rate of forest cover change, namely y = 0.017 + 0.00040x9 with SR of 17.3% and R2 is 88.0%. The study concludes that the most significant factor affecting the natural forest cover change in the study site is the proximity of the district's capital city (x9). Therefore, a spatial mathematical model can facilitate the government in monitoring forest cover.